Cerebras

4 months ago

Kernel Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Build and optimize high-performance ML and HPC kernels that run on Cerebras’ massively parallel AI chip architecture. You’ll design kernel specifications for machine learning and linear algebra workloads, develop and debug low-level assembly and a custom C-like CSL language library, and measure performance to guide design decisions. Partner with hardware and system architects to tune instruction sets, microarchitecture, and IO, and establish unit/system testing to validate correctness and performance.

Location: United States, Canada

Workplace: Onsite

Employment Type: Full time

Job Function: Healthcare (Clinical, Medical, Wellness)

Key Responsibilities

•Develop design specifications for new machine learning and linear algebra kernels and map them to the Cerebras WSE system using parallel programming algorithms.
•Develop and debug an optimized kernel library using low-level assembly instruction and custom C-like (CSL) language routines.
•Implement and debug high-performance kernel routines in low-level assembly and CSL to optimize algorithms for the Cerebras hardware system.
•Use mathematical models and performance analysis to inform design decisions.
•Develop and integrate unit and system testing methodologies to verify kernel library functionality and performance, coordinating validation with the team.

Key Requirements

•Bachelor’s, Master’s, or PhD (or foreign equivalents) in Computer Science, Computer Engineering, Mathematics, or a related field.
•Understanding of hardware architecture concepts and comfort learning a new hardware architecture.
•Proficiency in C++ and Python for kernel development and debugging.
•Good knowledge of library and/or API development best practices.
•Strong debugging skills for complex software stacks.

Experience:AIHPCMachine learningDistributed systems

Education:Bachelor's in Computer Science, Computer Engineering, Mathematics, or related fields

Skills:DebuggingAnalysisProblem-solving

Tech Stack:C++PythonAssemblyCSLTensorFlowPyTorchGPUsFPGAs

Company Brief

Cerebras

Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn

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Cerebras

4 months ago

Kernel Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: United States, Canada

Workplace: Onsite

Employment Type: Full time

Job Function: Healthcare (Clinical, Medical, Wellness)

Key Responsibilities

•Develop design specifications for new machine learning and linear algebra kernels and map them to the Cerebras WSE system using parallel programming algorithms.
•Develop and debug an optimized kernel library using low-level assembly instruction and custom C-like (CSL) language routines.
•Implement and debug high-performance kernel routines in low-level assembly and CSL to optimize algorithms for the Cerebras hardware system.
•Use mathematical models and performance analysis to inform design decisions.
•Develop and integrate unit and system testing methodologies to verify kernel library functionality and performance, coordinating validation with the team.

Key Requirements

•Bachelor’s, Master’s, or PhD (or foreign equivalents) in Computer Science, Computer Engineering, Mathematics, or a related field.
•Understanding of hardware architecture concepts and comfort learning a new hardware architecture.
•Proficiency in C++ and Python for kernel development and debugging.
•Good knowledge of library and/or API development best practices.
•Strong debugging skills for complex software stacks.

Experience:AIHPCMachine learningDistributed systems

Education:Bachelor's in Computer Science, Computer Engineering, Mathematics, or related fields

Skills:DebuggingAnalysisProblem-solving

Tech Stack:C++PythonAssemblyCSLTensorFlowPyTorchGPUsFPGAs

Company Brief

Cerebras

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn